mirror of
https://github.com/explosion/spaCy.git
synced 2024-09-21 11:29:13 +03:00
33 lines
990 B
Python
33 lines
990 B
Python
from pydantic import StrictInt
|
|
from thinc.api import Model, chain, list2array, Linear, zero_init, use_ops
|
|
|
|
from ...util import registry
|
|
from .._layers import PrecomputableAffine
|
|
from ...syntax._parser_model import ParserModel
|
|
|
|
|
|
@registry.architectures.register("spacy.TransitionBasedParser.v1")
|
|
def build_tb_parser_model(
|
|
tok2vec: Model,
|
|
nr_feature_tokens: StrictInt,
|
|
hidden_width: StrictInt,
|
|
maxout_pieces: StrictInt,
|
|
nO=None,
|
|
):
|
|
token_vector_width = tok2vec.get_dim("nO")
|
|
tok2vec = chain(tok2vec, list2array())
|
|
tok2vec.set_dim("nO", token_vector_width)
|
|
|
|
lower = PrecomputableAffine(
|
|
nO=hidden_width,
|
|
nF=nr_feature_tokens,
|
|
nI=tok2vec.get_dim("nO"),
|
|
nP=maxout_pieces,
|
|
)
|
|
lower.set_dim("nP", maxout_pieces)
|
|
with use_ops("numpy"):
|
|
# Initialize weights at zero, as it's a classification layer.
|
|
upper = Linear(nO=nO, init_W=zero_init)
|
|
model = ParserModel(tok2vec, lower, upper)
|
|
return model
|